Level of depression and its associated factors among the frontline physicians of Bangladesh during the COVID-19 outbreak

The COVID-19 pandemic has exposed the frontline physicians to a greater risk of getting infected, tremendous workload, and drastic changes in their work environment, leading to an increased prevalence of depression among doctors from many countries, including Bangladesh. The aim of this study was to examine the association of various personal, professional and psychosocial factors with different degrees of depressive symptoms among the frontline doctors of Bangladesh working during the COVID-19 pandemic. An online, cross-sectional survey was conducted for that purpose and data were collected from 312 doctors working in Bangladeshi hospitals using a self-administered survey questionnaire inclusive of a validated tool (Patient Health Questionnaire-9). Among the participants, around half were of age 30-34 years (51.3%), 81.8% worked in public hospitals and 70.5% did not have any comorbidity. Regarding workplace conditions, 77% of the doctors reported a perceived shortage of healthcare providers at their workplace, while 95% reported a perceived shortage of equipment, most commonly N95 masks (49%), gowns (35%), eye-protective shields (35%). A total of 199 (63.8%) participants received formal training since the beginning of the pandemic. According to the response from PHQ-9 questionnaire, 17 (5%) participants reported having no depression, while 18 (6%), 18 (6%), 25 (8%), and 234 (75%) reported having mild, moderate, moderately severe, and severe depression. Findings from multiple logistic regression showed the odds of moderate-to-severe depression to be higher among physicians with comorbidities (OR:7.47, CI: 1.27-43.89, P: 0.026) and those who felt extremely worried from looking at negative news on social/mass media (aOR: 15.180, CI:1.98-116.683, P: 0.009). To preserve and promote the psychological well-being of Bangladeshi doctors, it is, therefore, crucial to take these identified sources and risk factors of depression under sincere consideration by the responsible authorities and appropriate measures should be designed to remove these sources of depression to better support the physicians of the country. © 2023, Mahidol University - ASEAN Institute for Health Development. All rights reserved.

Structural and Functional Analyses of SARS COV-2 RNA-dependent RNA Polymerase Protein and Complementary vs. Synthetic Drugs against COVID-19 and the Exploration of Binding Sites for Docking, Molecular Dynamics Simulation, and Density Functional Theory Studies

Background: RNA-dependent RNA polymerase (RdRp) contributes to the transcription cycle of the SARS-CoV-2 virus with the possible assistance of nsp-7-8 cofactors. Objective(s): The study aims to investigate the viral protective effects of complementary drugs in computational approaches that use viral proteins. Method(s): For the in silico studies, the identified compounds were subjected to molecular docking with RdRp protein followed by structural and functional analyses, density functional theory (DFT), and molecular dynamics (MD) simulation. The 3D structure of RdRp (6m71 PDB ID) was obtained from the protein databank as a target receptor. After reviewing the literature, 20 complementary and synthetic drugs were selected for docking studies. The top compounds were used for DFT and MD simulation at 200 ns. DFT of the compounds was calculated at B3LYP/6-311G (d, p) based on chemical properties, polarizability, and first-order hyperpolarizability. Results were analyzed using USCF Chimera, Discovery Studio, LigPlot, admetSAR, and mCule. Result(s): Computational studies confirmed the potent interaction of the complementary drugs forsythi-aside A, rhoifolin, and pectolinarin with RdRp. Common potential residues of RdRp (i.e., Thr-556, Tyr-619, Lys-621, Arg-624, Asn-691, and Asp-760) were observed for all three docking complexes with hydrogen bonding. Docking analysis showed strong key interactions, hydrogen bonding, and binding affinities (-8.4 to -8.5 kcal/mol) for these ligands over the FDA-approved drugs (-7.4 to -7.6 kcal/mol). Docking and simulation studies showed these residues in the binding domains. Conclusion(s): Significant outcomes of novel molecular interactions in docking, simulation, DFT, and binding domains in the structural and functional analyses of RdRp were observed. Copyright © 2022 Bentham Science Publishers.

Audit of Surgical Practice and Performance in COVID Crisis - Lessons for future

Aim: To evaluate the pattern of surgical emergencies and surgical care provided during COIVD 19 pandemic. Study design: Cross-sectional Study Place and duration of study: Department of Surgery, CMH, Lahore from 15th March - 15 June 2020. Methodology: Data was collected retrospectively, of all the patients who were admitted in department of surgery over the duration of 3 months. Demographic variables, diagnosis, work up related to COVID-19, specialty of admission and surgical vs conservative management was recorded. Results: A total of 312 patients were included. Majority were male 216(69.2%). Most of the patients 191(61.2%) were admitted via clinic, predominantly in month of May 148(41%). COVID-19 PCR was done on 210 patients (67.3%), chest x-ray was done on 271(87.9%), HRCT chest was done on 113 patients (29.20%). Although general surgery was the busiest service line with a total patient admission of 89(43.1%), Orthopedic surgery top the operative interventions list with 85.1% of admissions underwent operative management. Conclusion: The current local guidelines about patient flow and management of patients in COVID crisis are practical and can be implemented. In the wake of the later waves of COVID 19 hospitals should prepare to divert their resources to high volume specialties like General and orthopedic surgery. Simple, but important procedures like arteriovenous fistula creation should only be stopped it there is shortage of manpower.

Dentist's Knowledge and Behavior on the Use of Smart Phones in Clinical Environment and their association with Cross Infections

Background: The use of smart phones inside hospitals especially in clinically sensitive areas is a subject of debate because it may improve the quality of healthcare but can also be a vehicle of hospital acquired infections. Aim: To determine dentist's knowledge and behavior related to the use of smart phones in clinical environment and to determine the presence of microbial growth on these devices. Methods: This is a cross-sectional study in which validated survey tool was used to collect data about knowledge and behavior of 397 dental graduates from 8 dental colleges of Pakistan, regarding their usage of smart phones in clinical environment. Bacterial isolates were collected from the smart phones of 45 participants from Fatima Memorial Dental Hospital, Lahore. Results: The SPTC Scale was used to divide the participants into 3 categories;low, moderate and high users. The behavior related to smart phone usage in clinical environment was significantly different among the participants. Moderate users had significantly higher average behavior score of 3.7 (p-value = 0.034). The growth of pathogenic bacterial flora was greater on high users of smart phones (95%,) whereas those participants who were low users the percentage was 37%. Conclusion: Hospital-acquired infections (HAIs) are increasing significantly in number of patients and these can be prevented by adhering to proper hand hygiene practices and if hand hygiene is improved the amount of bacterial load will be less and disinfection of smart phone devices will not be required.

Covid-19 Detection by using Deep learning-based Custom Convolution Neural Network (CNN)

The early diagnosis and treatment of COVID-19 has been a challenge all over the world. It is challenging to manufacture many testing kits and even then, their accuracy rate is very low. Studies carried out recently show that chest x-ray images are of great help in the diagnosis of COVID-19. In this study, we have developed a COVID-19 detection model that by observing the chest x-ray images of the patient, detects that either the patient is affected by COVID-19 or not. The model is developed using a custom Convolutional Neural Network (CNN) that differentiates between COVID-19 and healthy x-ray images so that the patient can be diagnosed and quarantined on time to prevent the spread of the pandemic. We used two different datasets which are publicly available for the training and validation of this model. Upon completion, the proposed model yields an accuracy of almost 98%. Upon further training, our model will be able to be used as a COVID-19 detection tool in hospitals worldwide and will play a vital role in early detection and timely containment of the pandemic.

Evaluation of Transfer Learning for Mask Detection

The use of masks has become crucial in combating the Coronavirus pandemic. Unfortunately, the regulation of wearing a mask is not being upheld by many citizens which is contributing to the spread of the disease. To aid the efforts of regulations and to maintain safety in public areas, both large like parks or small like public transport, Artificial Intelligent systems can play a vital role. In this article, we explore the use of transfer learning across 5 models (Mobile Net V2, InceptionV3, Resnet50V2, VGG16 and DenseNet121) and measure their effectiveness in mask detection. Due to the lack of a large, diverse and annotated dataset, we explore the use of transfer learning using supervised methods and present the results of the experiments upon the Keras open-sourced models. We find an average of 99% accuracy for all 5 models. However, when we use K-Fold Cross Validation to account for bias, we find significant differences in results with the highest accuracy being achieved by VGG16 at 98.6%. With the mixture of the standard method of training and testing alongside K-Fold Cross Validation, we present our findings for the use of transfer learning for mask detection. © 2022. Zahin Akram, Arifuzzaman Arman, Mohammad Rakib Imtiaz and Syed Athar Bin Amir. This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.

Effect of covid-19 pandemic on non-covid illness in the general population of pakistan

Aim: The goal of this study was to examine the influence of the Covid-19 pandemic 2020 on the health-seeking behavior of the general public in a lower-middle-income nation like Pakistan by looking at the availability, accessibility, and usage of health infrastructure. Methodology: In this cross-sectional study, 394 Pakistani patients completed an online questionnaire measuring their willingness to seek medical treatment, reporting for follow-up visits, and the ease of getting medical care about their medical condition, both before and after the pandemic. The information was then examined. Results: During the pandemic, 21.8 percent of patients visited a health center for follow-up. Fear of infection from the health institution kept 20.3 percent of patients from showing up for follow-up. 17.5 percent of patients had significant symptoms from their underlying sickness but delayed going to the doctor due to the fear of the virus. Patients' appointments were canceled or rescheduled in 20.1 percent of cases, while 54.1 percent did not feel the need to visit a health center. Conclusion: Fear of the virus, lockdowns, limitations, and other reasons have resulted in a substantial proportion of the population avoiding ER/health facility visits while suffering symptoms that necessitate medical attention. The long-term impact on a developing country's healthcare system, such as Pakistan, will be negative unless extraordinary steps are made to provide safe, accessible, and cheap health care during the epidemic.